Add application file

app.py

@@ -0,0 +1,44 @@
+import torch
+
+# Check if a GPU is available
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+print(f"Using device: {device}")
+
+import gradio as gr
+
+# You can use this section to suppress warnings generated by your code:
+def warn(*args, **kwargs):
+    pass
+import warnings
+warnings.warn = warn
+warnings.filterwarnings('ignore')
+
+def retriever_qa(file, query):
+    # llm = get_llm()
+    # retriever_obj = retriever(file)
+    # qa = RetrievalQA.from_chain_type(llm=llm, 
+    #                                 chain_type="stuff", 
+    #                                 retriever=retriever_obj, 
+    #                                 return_source_documents=False)
+    # response = qa.invoke(query)
+    with open(file, 'r') as f:
+        first_line = f.readline()
+    
+    response = first_line + query
+    
+    return response
+
+rag_application = gr.Interface(
+    fn=retriever_qa,
+    allow_flagging="never",
+    inputs=[
+        # gr.File(label="Upload PDF File", file_count="single", file_types=['.pdf'], type="filepath"),  # Drag and drop file upload
+        gr.File(label="Upload txt File", file_count="single", file_types=['.txt'], type="filepath"),  # Drag and drop file upload
+        gr.Textbox(label="Input Query", lines=2, placeholder="Type your question here...")
+    ],
+    outputs=gr.Textbox(label="Output"),
+    title="RAG Chatbot",
+    description="Upload a PDF document and ask any question. The chatbot will try to answer using the provided document."
+)
+
+rag_application.launch(share=True)